This is a submission for the Agent.ai Challenge: Full-Stack Agent (See Details)
It also apply for Challenge: Productivity-Pro Agent
What I Built
I developed an interconnected system of AI agents designed to streamline the job search process, leveraging LinkedIn profiles as the foundation. The ecosystem consists of four specialized agents:
Main Job Search Agent
This is the core component that analyzes LinkedIn profiles and matches them with relevant job opportunities. Users can specify their target country, and the agent searches for positions that align with their skills and experience. It includes a subscription feature (as a call another AI Agent) for receiving weekly job matches.
CV Generator Agent
This versatile agent transforms LinkedIn profiles into polished, professional CVs. While it integrates with the broader ecosystem, it's also available as a standalone tool, offering flexibility for users who only need the CV creation functionality.
Job Subscription Manager Agent
This agent handles the subscription system, allowing users to subscribe
for receiving job updates.
Job Distribution Agent
This agent is responsible for the actual delivery of weekly job offers to subscribed users. It ensures that curated job listings reach users according to their subscription preferences.
The system creates a seamless experience where users can move from profile analysis to CV creation, job matching, and ongoing job alerts, all powered by AI to maximize relevance and efficiency in their job search.
Demo
https://agent.ai/agent/job-offer-finder
https://agent.ai/agent/cv-generator
https://agent.ai/agent/job-offer-subscription
https://agent.ai/agent/job-offer-cron-sender
AI Agents ecosystem
Main Agent - job offer finder:
Agent.ai Experience
My experience working with the Builder and AI Agents was overwhelmingly positive. I have used several features like calling APIs, utilizing AI capabilities, implementing loops, and using built-in data actions such as retrieving LinkedIn profiles. I was able to integrate it with Google Sheets to store data. The platform's flexibility enabled seamless integration with various services, while its intuitive interface accelerated development time.
The YouTube video tutorials proved invaluable in understanding key concepts and implementation techniques. The supportive community helped troubleshoot issues and shared useful tips for optimizing agent performance.
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